Graph Analysis and Visualization: Discovering Business Opportunity in Linked Data

Chapter 14 Big Data

Big Data has been at the center of much of the innovative research and development in the field of graph analytics and visualization. With so many of our social, consumer, and other exchanges occurring online, the amount of data being collected every day, as well as opportunities to link across data sets, stretches the limits of our ability to take full advantage of it. For businesses, the central problem is no longer getting better data, but getting better information out of data.

The term “Big Data” can mean different things to different people, but defining issues are generally agreed to include the four V’s—volume, velocity, variety, and veracity. Simply put, challenges exist with the size of data, how rapidly it is streaming in, how extremely multi-faceted it has become, and how uncertain some of the source or derived data can be. Big Data is not strictly defined by how big it is, but by the fact that it is large and complex enough that it defies management and analysis using traditional systems and approaches.

Traditional systems often store structured data in table form on a server. Queries are then used to slice and dice along dimensions for subsequent analysis. Analysis is done in the memory of a single machine, typically with facets displayed independently in separate views. In some of the more advanced tools, filtering and interactive cross-view highlighting provide the capability to explore relationships one at a time with dimensions ...